Dataset Card for SUMM-RE small

Manually corrected transcripts of French conversations, aligned with the audio signal.

Dataset Details

Dataset Description

The SUMM-RE dataset is a corpus of meeting-style conversations in French created for the purpose of the SUMM-RE project (ANR-20-CE23-0017). SUMM-RE small is a subset of the full SUMM-RE corpus for which the transcripts have been manually corrected and aligned with the audio down to phoneme level. It can be used for the evaluation of automatic speech recognition and voice activity detection models.

The SUMM-RE small subset consists of 10 randomly selected conversations. Each conversation lasts roughly 20 minutes and involves 3-4 speakers. Each participant has an individual microphone and associated .wav file leading to 39 audio files in all.

• Created by: The corpus was recorded and manually annotated by the Language and Speech Lab (LPL) at the University of Aix-Marseille, France.
• Funded by: The National Research Agency of France (ANR) for the SUMM-RE project (ANR-20-CE23-0017).
• Shared by: LINAGORA (coordinator of the SUMM-RE project)
• Language: French
• License: CC BY-SA 4.0

Dataset Sources

• Repository: Both gold corrected and automatic transcripts (produced with Whisper) can be found on Ortolang.
• Paper: [More Information Needed]

Uses

Direct Use

This version of SUMM-RE small is designed for the evaluation of automatic speech recognition models and voice activity detection for conversational, spoken French.

Out-of-Scope Use

Due to its size, the corpus is not suitable for model training.

Dataset Structure

• meeting_id, e.g. 001a_PARL, includes:
  • experiment number, e.g. 001
  • meeting order: a|b|c (there were three meetings per experiment)
  • experiment type: E (experiment) | P (pilot experiment)
  • scenario/topic: A|B|C|D|E
  • meeting type: R (reporting) | D (decision) | P (planning)
  • recording location: L (LPL) | H (H2C2 studio) | Z (Zoom) | D (at home)
• speaker_id
• audio_id: meeting_id + speaker_id
• audio: the .wav file for an individual speaker
• transcript: the manually corrected transcript (corrected from Whisper transcripts)
• ipus: a list of start and end times for manually annotated interpausal units (units of speech from a single speaker that are separated by silences above a certain threshold)
• words: a list of start and end times for each word
• phonemes: a list of start and end times for each phoneme

Dataset Creation

Curation Rationale

The full SUMM-RE corpus, which includes meeting summaries, is designed to train and evaluate models for meeting summarization. SUMM-RE small is an extract of this corpus used to evaluate various stages of the summarization pipeline, starting with automatic transcription of the audio signal.

Source Data

The SUMM-RE corpus is an original corpus designed by members of LINAGORA and the University of Aix-Marseille and recorded by the latter.

Data Collection and Processing

[More Information Needed]

Who are the source data producers?

Corpus design and production:

• University of Aix-Marseille: Océane Granier (corpus conception, recording, annotation), Laurent Prévot (corpus conception, annotatation, supervision), Hiroyoshi Yamasaki (corpus cleaning, alignment and anonymization), Roxanne Bertrand (corpus conception and annotation) with helpful input from Brigitte Bigi and Stéphane Rauzy.

• LINAGORA: Julie Hunter, Kate Thompson and Guokan Shang (corpus conception)

Corpus participants:

• Participants for the in-person conversations were recruited on the University of Aix-Marseille campus.
• Participants for the zoom meetings were recruited through Prolific.

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

Principal annotator: Océane Granier

Additional assistance from: Laurent Prévot, Hiroyoshi Yamasaki and Roxane Bertrand

Personal and Sensitive Information

The audio and transcripts have been (semi-automatically) anonymized.

Bias, Risks, and Limitations

[More Information Needed]

Recommendations

Citation [optional]

Hiroyoshi Yamasaki, Jérôme Louradour, Julie Hunter and Laurent Prévot (2023): "Transcribing and aligning conversational speech: A hybrid pipeline applied to French conversations," Workshop on Automatic Speech Recognition and Understanding.

BibTeX:

[More Information Needed]

APA:

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Glossary [optional]

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